ANR Project CAPTURES
Competition Among Providers for Telecommunication Users: Rivalry and Earning Stakes
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Updates:
August 24, 2009:
Publications and 2nd meeting.
March 12, 2009:
Results and publications.
Sept. 14, 2008:
First release: v1.0.
General information
The Internet has moved from an academic network to a commercial and highly competitive one where providers compete for customers by playing with the price to access service and the Quality of Service (QoS) they offer. There are now different ways to access the network through different technologies, using ADSL, FTTx, telephone network, CDMA wireless network, WiFi or WiMAX among others, with different QoS capabilities. Moreover, the convergence of networks, where Internet access, wired and wireless telephony, television are regrouped into a single network poses additional economic challenges. In this situation, each provider has to adapt its pricing scheme in order to attract customers, to maximize his revenue and/or to allow fairness in the way resources are shared. Pricing has been a hot topic in telecommunication networks during the last decade (due to congestion) and many schemes have been proposed in the literature. On the other hand competition among providers has received very little attention up to now. The goal of this project is to deal with that issue. Indeed, we need to study the distribution of customers among providers as a first level of game, and then to focus on a second higher level, the price and QoS war among providers.
Our goals are
- To provide models and analysis of direct competition among providers operating on the same or different technologies (being WiFi, WiMAX, 3G, ADSL…) and the dynamics of those models
- To deal with multi-homing, that is the possibility to use the different available technologies at the same time
- To discuss capacity expansion for providers from an economic point of view
- To analyse retention policies that prevent users from churning, and how this can be controlled
- To investigate how demand uncertainty impacts the above models.
- To study the impact of alliances/collusions among a given group of providers and define preventive regulation or incitation rules.